The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
Internal combustion engines generate drive torque by combusting an air and fuel mixture. More specifically, air is drawn into an intake manifold through a throttle. The air is distributed to cylinders and is mixed with fuel. The fuel and air mixture is compressed within a cylinder by a reciprocally driven piston. The compressed air and fuel mixture is combusted and the resultant combustion drive the piston within the cylinder, which rotatably drives a crankshaft.
Advancements of automotive engine technologies have resulted in engines that are equipped with advanced actuators and sensors, which provide increased control over engine operation. As a result, the basic engine operation has changed in order to improve fuel economy and to reduce emissions without sacrificing engine performance. These additional actuator inputs include, but are not limited to, cam phasers, variable valve lift, direct injection, cylinder deactivation, variable intake tuning and the like, and provide sizable improvement in fuel economy and emissions.
These additional degrees of engine control freedom, however, lead to a significant increase in engine mapping and calibration requirements during the engine design and control system development process. For this reason, a comprehensive methodology is needed to provide a systematic approach to assist the engine control system development and calibration processes within a math-based framework.
A traditional engine mapping and control methodology is disclosed in SAE Paper 950983 by Christopher Onder and Hans Geering, which describes an approach of modeling parameters in a combustion characterization function. The combustion characterization function is used to predict how combustion occurs at engine operating conditions where no test data is measured. The method disclosed in SAE Paper 950983, however, is primarily intended for obtaining initial spark timing and fueling quantity calibration maps for the optimal fuel economy in an engine with fixed cam timings. As a result, this method has limited application, and is not usable for engines with more complex control options. Further, predictions of the combustion parameters are performed in a vicinity of reference points, which causes discontinuities in the resulting combustion parameters whenever the model switches to different reference points. Finally, while the above-described method predicts combustion parameters relatively independent of engines used, the approach was limited to Spark-Ignition (SI) engines only, lacking the flexibility to be used for other engine types, such as Compression-ignition Direct-injection (CIDI) engines and Homogeneous-Charge Compression-Ignition (HCCI) engines.
Using such traditional methods, engine tests are conducted by adjusting a single input parameter, while maintaining all of the other parameters constant. Consequently, the number of experiments quickly reaches a level for which it would be practically impossible to carry out all of the experiments in an actual engine setup. This becomes even more apparent when the engine is equipped with today's advanced actuators, e.g. dual cam phasers, variable valve lift, high-pressure direct-injection, etc. As an example, assume that there are five control input parameters (throttle angle, intake/exhaust cam positions, spark timing, and fuel injection) and one engine operating setpoint (engine speed). Assuming the stoichiometric air/fuel ratio operations at all time, there are still four control inputs and one engine operating setpoint that can continuously vary within the operating ranges. Therefore, considering seven levels for each of the input parameters, 16807 test cases (=75) would be required for the engine experiments.